| تعداد نشریات | 285 |
| تعداد نشریات سازمان | 83 |
| تعداد شمارهها | 3,139 |
| تعداد مقالات | 34,918 |
| تعداد مشاهده مقاله | 50,383,620 |
| تعداد دریافت فایل اصل مقاله | 90,276,991 |
بررسی امکان تهیه نقشه شدت خشکیدگی جنگلهای بلوط زاگرس با استفاده از دادههای ماهوارهای Worldview-2 (مطالعه موردی: جنگلهای شهرستان ایلام) | ||
| تحقیقات جنگل و صنوبر ایران | ||
| مقاله 10، دوره 25، شماره 3 - شماره پیاپی 69، مهر 1396، صفحه 452-462 اصل مقاله (928.08 K) | ||
| نوع مقاله: علمی- پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/ijfpr.2017.112879 | ||
| نویسندگان | ||
| امید کرمی1؛ اصغر فلاح* 2؛ شعبان شتایی3؛ هومن لطیفی4 | ||
| 1دانشجوی دکتری، گروه علوم جنگل، دانشکده منابع طبیعی، دانشگاه علوم کشاورزی و منابع طبیعی ساری، ساری، ایران | ||
| 2دانشیار، گروه علوم جنگل، دانشکده منابع طبیعی، دانشگاه علوم کشاورزی و منابع طبیعی ساری، ساری، ایران | ||
| 3دانشیار، گروه جنگل داری، دانشکده علوم جنگل، دانشگاه علوم کشاورزی و منابع طبیعی گرگان، گرگان، ایران | ||
| 4استادیار، گروه جغرافیا و زمینشناسی، دانشگاه ووتزبورگ، ووتزبورگ، آلمان | ||
| چکیده | ||
| طی سالهای اخیر پدیده زوال بلوط به جنگلهای زاگرس آسیب جدی رسانده است. برای مقابله و مدیریت این بحران قبل از هر چیزی نیاز به اطلاعات دقیقی از وضعیت و گستره وقوع این پدیده در سطح جنگل است. یکی از راههای مؤثر برای دستیابی به اطلاعات مربوط به گستره و شدت وقوع خشکیدگی در جنگل در محدودههای وسیع استفاده از دادههای ماهوارهای است. در این پژوهش که در قسمتی از جنگلهای شهرستان ایلام انجام شد، با استفاده از دادههای ماهوارهای Worldview-2 به تهیه نقشه شدت خشکیدگی جنگل در چهار طبقه پرداخته شد و از چهار الگوریتم طبقهبندی حداکثر احتمال، بیز ساده، نزدیکترین همسایه و شبکه عصبی مصنوعی برای طبقهبندی دادههای ماهوارهای استفاده شد. نتایج نشان داد که از بین روشهای مختلف، روش الگوریتم شبکه عصبی مصنوعی با صحت کلی 72/83 درصد بهترین نتایج را داشت. نتایج این پژوهش نشان داد که دادههای سنجنده WV-2 میتوانند بهخوبی شدت وقوع زوال بلوط را نشان دهند. | ||
| کلیدواژهها | ||
| زوال بلوط؛ سنجش از دور؛ شبکه عصبی مصنوعی | ||
| عنوان مقاله [English] | ||
| Investigation on the feasibility of mapping of oak forest dieback severity using Worldview-2 satellite data (Case study: Ilam forests) | ||
| نویسندگان [English] | ||
| Omid Karami1؛ Asghar Fallah2؛ Shaban Shataei3؛ Hooman Latifi4 | ||
| 1Ph.D. Student, Department of Forest Sciences, Faculty of Natural Resources, Sari Agricultural Sciences and Natural Resources University, Sari, Iran | ||
| 2Associate Prof., Department of Forest Sciences, Faculty of Natural Resources, Sari Agricultural Sciences and Natural Resources University, Sari, Iran | ||
| 3Associate Prof., Department of Forestry, Faculty of Forest Sciences, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran | ||
| 4Assistant Prof., Department for Geography and Geology, University of Wuerzburg, Wuerzburg, Germany | ||
| چکیده [English] | ||
| In recent years, oak decline phenomenon has caused severe damages in Zagros forests. To deal with and managed this crisis, prior to any action, having accurate information about the status and distribution area of this phenomena is necessary. Using satellite data is one of methods to achieve information on the extent and severity of die back. For this purpose, map of oak decline severity was prepared in four levels for some parts of Ilam forests using Worldview-2 satellite data. Maximum likelihood, naive bayes, K-nearest neighbors and artificial neural network classification algorithm were used. The results showed that among different classification methods, the results of artificial neural network classification algorithm had most overall accuracy with 72.83%. Moreover, our results confirmed that the Worldview-2 satellite data can illustrate the severity of oak decline. | ||
| کلیدواژهها [English] | ||
| Artificial Neural Network, oak decline, Remote Sensing | ||
| مراجع | ||
|
- Aci, M., Inan, C. and Avci, M., 2010. A hybrid classification method of k nearest neighbor, Bayesian methods and genetic algorithm. Expert Systems with Applications, 37(7): 5061-5067. - Baguskas, S.A., Peterson, S.H., Bookhagen, B. and Still, C.J., 2014. Evaluating spatial patterns of drought-induced tree mortality in a coastal California pine forest. Forest Ecology and Management, 315: 43-53. - Barazmand, S., Shataee Joybari, Sh. and Abdi, O., 2012. Recognition possibility of trees canopy die back using high resolution satellite image of Quick bird (Case study: Shastkolate forest, Gorgan). Iranian Journal of Forest and Poplar Research, 19(4): 466-477 (In Persian). - Cho, M.A., Malahlela, O. and Ramoelo, A., 2015. Assessing the utility WorldView-2 imagery for tree species mapping in South African subtropical humid forest and the conservation implications: Dukuduku forest patch as case study. International Journal of Applied Earth Observation and Geoinformation, 38: 349-357. - Chuanga, W.C., Lina, C.Y., Chiena, C.H. and Choub, W.C., 2011. Application of Markov-chain model for vegetation restoration assessment at landslide areas caused by a catastrophic earthquake in central Taiwan. Ecological Modelling, 222: 835-845. - Deshayes, M., Guyon, D., Jeanjean, H., Stach, N., Jolly, A. and Hagolle, O., 2006. The contribution of remote sensing to the assessment of drought effects in forest ecosystems. Annals of Forest Science, 63: 579-595. - Fassnacht, F.E., Latifi, H., Ghosh, A., Joshi, P.K. and Koch, B., 2014. Assessing the potential of hyperspectral imagery to map bark beetle-induced tree mortality. Remote Sensing of Environment, 140: 533-548. - Hosseini, A., Hosseini, S.M., Rahmani, A. and Azadfar, D., 2014. Comparison between two oak stands (Healthy and affected by oak decline) in respect to characteristics of competitive environments at Ilam province. Iranian Journal of Forest and Poplar Research, 21(4): 565-577 (In Persian). - Ismail, R., 2009. Remote sensing of forest health: the detection and mapping of Pinus patula trees infested by Sirex noctilio. Ph.D. thesis, School of Environmental Sciences, University of KwaZulu-Natal, Pietermaritzburg, South Africa, 161p. - Joria, P.E. and Ahearn, S.C., 1991. A comparison of the SPOT and Landsat Thematic Mapper satellite systems for detecting gypsy moth defoliation in Michigan. Photogrammetric Engineering & Remote Sensing, 57: 1605-1612. - Kotsiantis, S.B., 2007. Supervised Machine Learning: A review of classification techniques. Informatica, 31: 249-268. - Levesque, J. and King, D., 2003. Spatial analysis of radiometric fractions from high-resolution multispectral imagery for modelling individual tree crown and forest canopy structure and health. Remote Sensing of Environment, 84: 589-602. - Liu, D., Kelly, M. and Gong, P., 2006. A spatial-temporal approach to monitoring forest disease spread using multi-temporal high spatial resolution imagery. Remote Sensing of Environment, 101: 167-180. - McCoy, R.M., 2005. Field Methods in Remote Sensing. The Guilford Press, New York, 177p. - McGlone, J.C., 2004. Manual of Photogrammetry. 5th Edition, American Society for Photogrammetry and Remote Sensing Press, USA, 1151p. - Meddens, A.J.H., Hicke, J.A., Vierling, L.A. and Hudak, A.T., 2013. Evaluating methods to detect bark beetle-caused tree mortality using single-date and multi-date Landsat imagery. Remote Sensing of Environment, 132: 49-58. - Mir-Abolfathi, M., 2013. Outbreak of charcoal disease on Quercus spp and Zelkova Carpinifolia trees in forests of Zagros and Alborz mountains in Iran. Iranian Journal of Plant Pathology, 49(2): 257-263 (In Persian). - Pal, M. and Mather, P.M., 2003. An assessment of the effectiveness of decision tree methods for land cover classification. Remote Sensing of Environment, 86: 554-565. - Quirós, E., Felicísimo, Á.M. and Cuartero, A., 2009. Testing multivariate adaptive regression splines (MARS) as a method of land cover classification of TERRA-ASTER satellite images. Sensors, 9: 9011-9028. - Rafiei, Y., Alavi-Panah, S.K., Malek-Mohammadi, B., Ramezani-Mehraban, M. and Nasiri, H., 2012. Mapping of land cover using remote sensing by using of decision tree algorithm (Case study: national park and wildlife shelter of Bakhtegan). Geography and Environmental Planning, 47: 94-110 (In Persian). - Sánchez, M.E., Caetano, P., Ferraz, J. and Trapero, A., 2002. Phytophthora disease of Quercus ilex in southwestern Spain. Forest Pathology, 32: 5-18. - Shahi, K., Shafri, H.Z.M., Taherzadeh, E., Shattri Mansor, Sh. and Muniandy, R., 2015. A novel spectral index to automatically extract road networks from WorldView-2 satellite imagery. The Egyptian Journal of Remote Sensing and Space Science, 18(1): 27-33. - Shiraishi, T., Motohka, T., Thapa, R.B., Watanabe, M. and Shimada, M., 2014. Comparative assessment of supervised classifiers for land use-land cover classification in a tropical region using time-series PALSAR mosaic data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(4): 1186-1199. - Sims, D.A. and Gamon, J.A., 2002. Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages. Remote Sensing of Environment, 81(2-3): 337-354. - Stone, C. and Coops, N.C., 2004. Assessment and monitoring of damage from insects in Australian eucalypt forests and commercial plantations. Austral Journal of Entomology, 43: 283-292. - Tsangaratos, P. and Ilia, I., 2016. Comparison of a logistic regression and Naïve Bayes classifier in landslide susceptibility assessments: the influence of models complexity and training dataset size. Catena, 145: 164-179. - Waser, L.T., Küchler, M., Jütte, K. and Stampfer, T., 2014. Evaluating the potential of WorldView-2 data to classify tree species and different levels of Ash mortality. Remote Sensing, 6: 4515-4545. - Zakeri Anaraki, S. and Fallah Shamsi, S.R., 2014. An investigation on Persian Oak (Quercus brantii Lindl) single tree defoliation mapping, using Rapideye and Aster-L1B satellite imageries. Iranian Journal of Forest, 5(4): 443-456 (In Persian). | ||
|
آمار تعداد مشاهده مقاله: 1,486 تعداد دریافت فایل اصل مقاله: 1,273 |
||